This invention relates to method, procedure, algorithm, system, and computer program for improving and attempting to optimize the performance of marketing campaigns in which advertisements or other messages are distributed over an interactive measurable medium such as the Internet. When the message is an advertisement, the campaign involves a list of ad alternatives and a target customer population. The goal of the marketer is to allocate the ad alternatives to the customer population to optimize business objectives such as maximizing the number of responses received. When the message is other than an advertisement, the goal is to otherwise allocate messages to optimize analogous business or campaign objectives, typically measured by the number of successes or successful responses. In this description, the term “ad” has the same meaning and is used interchangeably with the term “advertisement”.
In large part due to the particular applicability of the invention to advertisements on the Internet, this background description focuses on internet advertising to establish one context of the invention and to differentiate the invention from conventional systems and methods. It is to be understood however, that the invention is not to be interpreted to be limited only to an Internet advertising environment.
Various systems currently exist for the delivery and tracking of advertisements on the internet, for instance, ad servers for serving and tracking “banner ads” on a web page. The users of these ad delivery or ad server systems have access to data on the performance of all the ads on all the locations. This data is updated by the delivery and tracking system on a periodic basis. The users are also provided with an array of parameters to configure the delivery and tracking system. In a typical conventional situation, an advertiser buys advertising space (ad space) on a number of web sites. The advertising space buy on each web site consists of a number of categories. Such categories may correspond to different sections within that web site, where a section is a specific web page or a set of related web pages within the site. A category may also correspond to keywords searched by a customer on a search engine. The term “zone” will be used to represent a unique site and category combination. There may typically be a number of banners that an advertiser wishes to deploy across these zones. A banner is either a graphic image that announces the name or identity of a site or is an advertising image. An impression occurs when an Internet visitor sees a banner. A clickthrough occurs when a visitor to a zone clicks on a banner. This redirects the visitor to the page on the advertiser's web site.
The term “placement” is used to refer to a particular banner-zone combination. The fraction of impressions (relative to the total number of impressions associated with the particular zone) that should be allocated to a particular banner alternative is an important placement parameter that the advertiser can select and modify, to boost the advertising campaign performance.
Impressions can occur at any time—whenever someone visits the appropriate page of a web site. However, the reports are typically updated at discrete times. We will call the intermediate time between two reports a stage. At the end of each stage, the results are available for that stage. In particular, the following information is available for each placement: (1) the number of impressions delivered during a stage, and (2) the number of clickthroughs generated during a stage.
Additionally this information (that is, the number of impressions delivered during a stage, and number of clickthroughs generated during a stage) may be available separately for: (a) different time slots within a stage (e.g. hour of day, if each stage is a day); (b) different frequency levels i.e. the number of times that an ad was seen by the customer; (c) different operating systems used by the machine on which the customer is logged on; (d) different interne browsers used by the customer; and (e) different domain addresses of the computer on which the customer is logged on. This list is exemplary and not intended to be exhaustive.
In conventional systems and methods, these reports are provided in printed form or in the electronic equivalent of printed form, and are manually analyzed by trained analysis personnel to derive new, improved advertisement configurations. For example, they are analyzed in an attempt to optimize the clickthroughs generated by a pool of banner alternatives for a given zone, a given frequency level, and the like configuration information. This manual process is tedious and error-prone and has an inherent delay between the period of data collection and the time new advertisements are to be placed because of the large amount of data to be analyzed and the large number of parameters to be modified. Even if errors are not made and the user is able to overcome the tedium of the process, it is unlikely to yield optimal or even near-optimal recommendations for advertisement configurations. This is especially true in light of the typical delay of from a day to a week that elapses between data collection, analysis, and a new or modified ad campaign based on the analysis.
Optimization to provide an effective advertising campaign is in essence a multi-dimensional optimization problem, that by-and-large cannot be timely solved using conventional tools, methods, or systems. It is noted that these problems exist substantially independent of the type of advertisement or message, and that such issues and problems exist relative to advertisements for products and services, political campaigns, ballot measures and initiatives, media programming, lobbying, surveys, polling, news headlines, sports scores, as well as other directed marketing, promotions, surveys, news, information, other content generally, and the like.
Therefore, there remains a need for an automated system for optimizing allocation parameters for advertisement alternatives or message alternatives. There also remains a need for an automated system and method for rapidly and efficiently executing the optimized allocation parameters to place the advertisement or message on the Internet or other local or global communication system. More particularly there remains a need for an optimization procedure or algorithm that utilizes available message performance information (for example, ad performance information) and generates recommendations for maintaining good performance or for improving performance during a subsequent stage of the campaign or optimizing performance of the entire campaign.
There also remains a need for a system and method that can learn and optimize across the various other parameters that can be reconfigured in advertisement delivery systems also commonly referred to as ad servers. For example, there remains a need for an ad server system and method that permits an advertiser to display different banners (or other content or messages) based on a time-of-day user web browsing profile which may include geographic location information, demographic information, or the like, as well as other user targeting information.
There also remains a need for an operating model that provides the optimized allocations for banner ad alternatives or message alternatives automatically on an interconnected network of computers or other information devices or appliances without significant human intervention.
These and other needs in conventional systems and methods are solved by the inventive system and method, particularly by the inventive optimization method and algorithm and computer software implementations of the inventive optimization algorithm and method.